There is an emergence of a growing number of applications and services based on spatiotemporal data in the most diverse areas of knowledge and human activity. The Internet of Things (IoT), the emergence of technologies that make it possible to collect information about the evolution of real world phenomena and the widespread use of devices that can use the Global Positioning System (GPS), such as smartphones and navigation systems, suggest that the volume and value of these data will increase significantly in the future. It is necessary to develop tools capable of extracting knowledge from these data and for this it is necessary to manage them: represent, manipulate, analyze and store, in an efficient way. But this data can be complex, its management is not trivial and there is not yet a complete system capable of performing this task. Works on moving points, that represent the position of objects over time, are frequent in the literature. On the contrary there are much less solutions for the representation of moving regions, that represent the continuous changes in position, shape and extent of objects over time, e.g., storms, fires and icebergs. The representation of the evolution of moving regions is complex and requires the use of more elaborate techniques, e.g., morphing and interpolation techniques, capable of producing realistic and geometrically valid representations. In this dissertation we present and propose a data model for moving objects (moving points and moving regions), in particular for moving regions, based on the concept of mesh and compatible triangulation and rigid interpolation methods. This model was implemented in a framework that is not client or application dependent and we also implemented a spatiotemporal extension for PostgreSQL that uses this framework to manipulate and analyze moving objects, as a proof of concept that our framework works with real applications. The tests' results using real data, obtained from satellite images of the evolution of 2 icebergs over time, show that our data model works. Besides the results obtained one important contribution of this work is the development of a basic framework for moving objects that can be used as a basis for further investigation in this area. A few problems still remain that must be further studied and analyzed, in particular, the ones that were found when using the compatible triangulation and rigid interpolation methods with real data.
The objective of this study is to present a new constitutive model of plastic behaviour of metal sheet, which takes into account variables that may influence single and especially multistage operations. This new approach is based in models of texture and strain-path induced anisotropy that captures the influence of the microscopic physical mechanism, which governs the macroscopic plastic behaviour, i.e. crystallographic texture and dislocation structures. The obtained model is of vital importance for the development of an accurate finite element tool for virtual product development of all kinds of sheet metal parts. Such constitutive model has been integrated into a general-purpose finite element code. Two industrial relevant metal sheets of deep-drawing quality are considered in the present study: a low carbon steel and an aluminium sheet 5182. Detailed experimental studies have been performed to fully characterise their crystallographic texture and hardening behaviour upon strain path change. A simple test case for basic verification and experimental validation is defined. This test consists of a two-stage operation: a biaxial stretch followed by a uniaxial tension. Strain distributions and tensile curves have been experimentally assessed and they are compared to FE predictions.
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